A unified framework of perturbation and gradient-based attribution methods for Deep Neural Networks interpretability. DeepExplain also includes support for Shapley Values sampling. (ICLR 2018)
Another problem, if I load a model from file, I must predict one time before generating saliency maps ,otherwise it will raise an exception:
"tensorflow.python.framework.errors_impl.InternalError: Blas SGEMM launch failed : m=21609, n=128, k=64
But if I use this model to predict one time, after that DeepExplain run well.
Another problem, if I load a model from file, I must predict one time before generating saliency maps ,otherwise it will raise an exception: "tensorflow.python.framework.errors_impl.InternalError: Blas SGEMM launch failed : m=21609, n=128, k=64
But if I use this model to predict one time, after that DeepExplain run well.
Originally posted by @linchundan88 in https://github.com/marcoancona/DeepExplain/issues/36#issuecomment-473619493